7 Python Data Visualization Libraries in 15 minutes

In this video Rob, a Kaggle Grandmaster, quickly and humorously walks through each of the popular plotting and data visualization tools in python. These include bokeh, matplottlib, plotly, altir and seaborn. This video will give you an overview of each python package, what each does well and what they don't do well. Python is the #1 coding language for data science and has been growing over the years as an essential tool, especailly important for data visualization. Explained in a funny way every package is discussed in less than 15 minutes.
Timestamps:
00:00 Introduction
00:33 Matplotlib
02:46 Seaborn
05:10 Bokeh
07:50 Plotly Express
11:40 Plotnine
13:02 Altair
13:24 Pandas
14:09 Summary
Follow me on twitch for live coding streams: / medallionstallion_
Intro to Pandas video: • A Gentle Introduction ...
Exploritory Data Analysis Video: • Exploratory Data Analy...
Link to kaggle notebook used in the tutorial: www.kaggle.com/robikscube/all...
* KZbin: / @robmulla
* Twitch: / medallionstallion_
* Twitter: / medalliondata
* Kaggle: www.kaggle.com/robikscube
#DataScience #Python #DataViz

[@robmulla]

Because youtube doesn't seem to be showing my chapters in the videos here are the timeline links: 00:00 Introduction 00:33 Matplotlib 02:46 Seaborn 05:10 Bokeh 07:50 Plotly Express 11:40 Plotnine 13:02 Altair 13:24 Pandas 14:09 Summary

[@gschnuuget]

this is an amazing overview, thank you very much for this video! I especially like that you are presenting in dark mode 🙂

[@robmulla]

Glad you liked it! I appreciate the feedback.

[@brandonwarfield5611]

I don't know how you made this entertaining! I was chuckling all the way through the video.

[@robmulla]

Haha. Thanks Brandon. Glad you enjoyed it.

[@subbyspersonalvlog7143]

It was worth a lot in just one lovely video imparting so much of value as you present things vividly in a very attractive way. Given enough time, I enjoy watching all your videos, multiple times if need be.

[@robmulla]

Glad you enjoyed it! This video is a little more silly than my other ones

[@cedric1731]

What also makes bokeh cool is it's ability to handle big data better than some alternatives

[@robmulla]

That’s a good note I didn’t realize!

[@kikfraben1]

Didn’t know that charts can be so much fun, awesome video!

[@askthenickman]

Love the energy. Thanks!

[@BrianKamanzi]

Great video, exactly what I was looking for and positive energy to boot, appreciated.

[@mschuer100]

Thank you Rob, another great video. Was never aware that PlotNine existed, will have to check it out. Also want to dig more into Ploty's scatter_map.....knew it existed but never used it...this gives me a reason to check it out. Keep the great videos coming please, they are very useful.

[@robmulla]

Glad you learned a few new things from this video. My hope was to show a lot of what's out there so you know it's there to use in the future.

[@mschuer100]

@@robmulla and a great job you did. Thanks!

[@mdd6197]

really helpful vid I mainly just plot in pandas like you said it saves you time lol but I did not know what I was missing out on with the interactive plots

[@robmulla]

Thanks so much for the feedback. Glad you learned something new about interactive plots. 🙌

[@RHHS1985]

Thanks a lot Rob ! Any suggestions to create Concept Maps, Mind Maps or Entity Relashionships diagrams, for Data Governance purposes ?

[@milindankur]

I love to watch Rob Mulla! All these plots are so beautiful! Thanks for summarizing them. Respect🤟

[@robmulla]

Glad you liked it! Appreciate the compliment.

[@carlosernestocustodiocaden777]

Excelente vídeo, es cosa de empezar a practicar, hasta encontrar lo mejor para el trabajo que hay que hacer.

[@robmulla]

Muchas gracias!

[@TheSoonAnn]

great way to introduce all the packages available , now i know the gg plot equivalent in python

[@user-iv9zu4oh8i]

Nice. I was surprised that you did not include LUX at this cool overview.

[@hfuhruhurr]

Altair's (two syllables, btw) syntax makes the most sense to me. Took me forever to understand how to unleash the power, though.

[@robmulla]

I didn’t realize that. I haven’t used it much before. Why is it so powerful?

[@nulencode7660]

@@robmulla For Altair, I would say the syntax follows the same logic than Seaborn, but the advantage is that you can make more beautiful and **interactive** plot that are easy to embed in a webpage.

[@williamgriffin61]

great content! thanks you Rob!

[@robmulla]

Thanks for watching.

[@tariqaziz1795]

Thanks for knowlege and entertain. i hope to learn much more.

[@robmulla]

Glad you were both entertained and learned! That’s my goal.

[@DANIEL-lt9br]

Thanks for this video, i have been enjoyed a lot, i'm subscribed yet!

[@robmulla]

Really appreciate that!

[@RaptorT1V]

Вот это сразу лайк. Контент интересный и полезный. Для моего исследования в самый раз

[@johnmachabee7261]

You earned my subscription, good sir!

[@robmulla]

Thanks for watching.

[@gerardbender197]

Thank you That was so helpful

[@robmulla]

Glad it helped! Thanks so much for the comment.

[@chuang6248]

Plotly Express is awesome! that it what i need! thank you !

[@robmulla]

Glad you found what you were looking for!

[@khanafridi8894]

Sir plz make an amazing series about visualization in python and some other important graph 😊

[@joshuaharkness2630]

Can you add a plotly visualization to PowerPoint? I have been able to do this using a PNG of the graph, but would love to keep it interactive.

[@kalif350]

Excellent video. Thanks!

[@robmulla]

Glad you liked it!

[@agnichatian]

If the GUI of my app is a web page, can I put these plots on it ? If so, can they be interactive ? i.e. process in Python,, render as web...

[@coopernik]

That was a good video. I subscribed

[@robmulla]

Thanks!

[@martinnjeri6997]

so nobody is gonna say something about those violin plots?? they look just like..... never mind!! Niice video Maestro... Learning a lot from you!! Kudos ....

[@robmulla]

🙊🙈 Thanks for watching.

[@Grenouille3344]

Hi, I search to show a chart of data same as Nasdaq and it can update with new data live in real time. Can you tell me the best for that. I appreciate a lot.

[@dimitriosdesmos4699]

Which is best for plotting live data from exchanges?

[@robmulla]

Depends. How live?

[@soumyadrip]

LMFAO did not know GMs are allowed to be that funny, JK , pog video editing skill. Had no idea that Python had many visualization libraries.

[@robmulla]

Glad you enjoyed it Somu! Trying to be a little less serious in this one.

[@cappy2112]

There are MANY more than he reviewed here though, close to 50 now

[@soumyadrip]

@@cappy2112 holy crap

[@geekyprogrammer4831]

@@robmulla Please continue to be make videos like this😊

[@robmulla]

@@geekyprogrammer4831 Thanks so much! Funny that this video has the least views of all that I made so I figured people didn't like the funny videos. Maybe I'll give it another try!

[@atulkumarsonu7082]

Thanks. Would like a video on Panel.

[@samarumugam4833]

Thanks Bro. Good Infos....

[@-steady-8215]

Did you ever make a video on dash then?

[@petehall1900]

Why is chart studio the new plotly import syntax?

[@robmulla]

I'm not sure if I'm following your question. Thanks for watching.

[@gabrielmoreno2554]

Love your work. PX😍

[@robmulla]

Thanks Gabriel! Glad you enjoy it.

[@pietraderdetective8953]

We can change Pandas plotting backend to Plotly if one need interactive chart

[@AdobadoFantastico]

bokeh looks fun

[@robmulla]

It is!

[@ajilaahad3508]

Bokeh is not working when ssl integrated. Can anyone help

[@sanishkoshijacob2813]

I used vispy for plotting real time data.

[@robosergTV]

where is proplot?

[@GlenCote]

How about Panel?

[@robmulla]

I haven’t heard of panel. Should I check it out?

[@jac.t.kitlim]

My vote on panel and the holoviz family..

[@Davidkiania]

Part of Hvplot.

[@TzviKD]

Really helpful! I think the title of the video can be improved for greater reach :)

[@robmulla]

Thanks! I’m open to ideas for a new title. Any suggestions?

[@TzviKD]

@@robmulla Sure.. "Matplotlib vs Seaborn vs Bokeh vs Plotly vs Plotnine vs Altair vs Pandas in 15 minutes" "7 Python Data Visualization Libraries in 15 minutes" "Data Visualization in Python - Quick Libraries Overview" As you can see, my line of thought is that the main subject of the video - the libraries - is not in the title.. but should be, because its an informative video and not entertainment; even though you did make it entertaining ;)

[@philwebb59]

5:16 Ryu Nagase, product management director, consumer imaging group, Canon Corp, pronounces bokeh like okay, with a b on front. BOW-kay. Stress on the BOW. kzbin.info/www/bejne/j2Glo5looZ2MqcU

[@robmulla]

Oh. I guess that’s the way it’s pronounced. Thanks for the feedback.

[@titan-0016]

content is good but those to b quirky jokes are not

[@stuartberg8030]

I'll give a shout-out for my favorites: holoviews and hvplot.pandas, which are built on top of bokeh and matplotlib. They give you a high-level API that makes lots of standard plots quickly, but you're free to customize the plot yourself with the lower-level library (bokeh or matplotlib) if you need extra control.

[@dhnguyen68]

I have closed your video… Just kidding, very nice explanation with lively humor. Thanks

[@bennguyen1313]

Do you have any suggestion for plotting 2d data real-time... with new samples coming in every 100ms (via can-bus)? I tried pyqtgraph, however with each new sample, the array took longer to display, and after just a couple minutes the lag was so bad that its not usable. Any suggestions on a tool that can keep up with an ever increasing data array? To minimize RAM, I was thinking of appending each new sample to a csv file, and then have maplotlib continuously reload the file. But maybe vaex is better at working with a dynamically increasing large data array ? Or maybe gnuplot, mayavi?

[@VIZA_9507]

Wheee i need to focus first as i beginner

[@zmd-code]

next time do this and check what happens with your colleagues: import pandas as plt import numpy as pd import matplotlib.pyplot as np

[@jonreznick5531]

Don't hate on pie charts, but yes they are bad wherever more than 6 categories are grouped and tallied.

[@robmulla]

Agree to disagree?

[@jonreznick5531]

now i want to hear you view on this. pie charts have treated me real good--the customers want them.

[@c0f2a]

import seaborn as sb

[@VIZA_9507]

I am beginner a in python

[@mikescarborough9196]

So violin plots should not be called twat plots…

[@jaxim1668]

really a fan of pandas aren't you?🤣

[@glawtonmoore]

Yellowbrick

[@VulcanOnWheels]

1:24 Really...? I'm outta here.

[@robmulla]

You love it.

[@user-jj5om7tq9k]

No, I was born in 1991

[@Zydres_Impaler]

I was born in 2003😂😂

[@NicolaBarbaro956]

cringe

[@robmulla]

Yep

[@GarzonG6]

Excellent content, stupid explanation

[@gabrielperfumo1122]

You are super cool!! Great content. My ranking: EDA: matplotlib, seaborn and pandas. PRESENTATIONS, DASHBOARDS AND WEBAPPS: Dash-plotly

[@robmulla]

So glad you like the content. Share with a friend or two! I totally agree with the seperation between EDA and presentation/dashboard libraries. Great point.